Forecasting Agent

Portfolio Forecasting Agent

Version: 1.0.0 Category: Financial Analysis / Portfolio Management Author: Claude Code Last Updated: November 22, 2025

Overview

Advanced portfolio forecasting system with multi-year projections, Monte Carlo simulations, tax planning, and comprehensive risk analysis. Designed for active trading portfolios with frequent position turnover.

Features

1. Multi-Year Projections

• 3-year and 5-year forward projections
• Three scenarios: Conservative, Baseline, Aggressive
• Monthly and quarterly breakdowns
• Compound growth modeling
• Tax-adjusted projections

2. Monte Carlo Simulations

• 1,000+ path simulations
• Probabilistic outcome distributions
• Milestone probability calculations
• Risk of ruin analysis
• Confidence intervals (50%, 95%, 99%)

3. Tax Forecasting

• Quarterly tax reserve calculations
• Federal + state tax obligations
• Multi-state comparison (NY vs FL/TX)
• Estimated payment schedules
• Tax-optimized withdrawal strategies

4. Risk Analysis

• Maximum drawdown calculations
• Monthly volatility metrics
• Sharpe ratio approximations
• Sensitivity analysis
• Scenario stress testing

5. Report Generation

• Professional PDF reports (LaTeX)
• Markdown analysis documents
• CSV data exports
• Interactive dashboards
• Google Drive integration

Usage

Quick 3-Year Projection

/forecast-portfolio

Output:

• 3-year baseline projection
• Monthly and quarterly breakdowns
• Tax reserve schedules
• Markdown summary report

Full 5-Year Analysis

/forecast-5year

Output:

• 5-year projection (all scenarios)
• Monte Carlo simulation (1,000 paths)
• Risk analysis
• Tax planning
• LaTeX PDF report

Monte Carlo Only

/forecast-monte-carlo --paths 1000 --months 60

Output:

• 1,000 simulation paths
• Percentile distributions
• Milestone probabilities
• Risk metrics

Sensitivity Analysis

/forecast-sensitivity --win-rate 80-95 --return 2-5

Output:

• Win rate impact table
• Return variance analysis
• Parameter sensitivity charts
• Optimal parameter identification

Tax Forecasting

/forecast-tax --years 5 --state NY

Output:

• Quarterly tax obligations
• Federal + state breakdown
• Payment schedule
• Multi-state comparisons

Configuration

Parameter File

Location: ~/projects/portfolio/PORTFOLIO_PARAMETERS_COMPLETE.yaml

Key Parameters:

trading:
  return_per_trade:
    all_time_avg: 3.58      # % per trade
  win_rate:
    actual: 90.0            # %
  trade_frequency:
    trades_per_month:
      conservative: 17
      baseline: 18.5
      aggressive: 20

account:
  initial_capital: 2000     # $
  monthly_deposits: 500     # $

tax:
  quarterly_extraction_pct: 37.0  # %

Scenarios

Conservative (17 trades/month)

• Lower trade frequency
• More defensive posture
• Realistic for part-time trading
• Final balance: $10.8M (5 years)

Baseline (18.5 trades/month)

• Historical average
• Sustainable frequency
• Default scenario
• Final balance: $8.98B (5 years)

Aggressive (20 trades/month)

• Maximum trade frequency
• Requires full-time focus
• Optimistic projections
• Final balance: $647B (5 years)

Key Calculations

Monthly Compounding

Monthly Return = (1 + Return_Per_Trade)^Trades_Per_Month - 1

Example (Baseline):
  = (1 + 0.0358)^18.5 - 1
  = 1.9096 - 1
  = 90.96% per month

Tax Reserve Extraction

Quarterly Gains = Ending_Balance - Starting_Balance - Deposits
Tax Reserve = Quarterly_Gains × 0.37
Portfolio Retained = Quarterly_Gains × 0.63

Monte Carlo Simulation

for each path:
    for each month:
        for each trade:
            if random() < win_rate:
                balance *= (1 + avg_winner%)
            else:
                balance *= (1 + avg_loser%)
        balance += monthly_deposit

Output Formats

1. Monthly Projection CSV

Columns:

• Month, Year, Quarter
• Starting Balance, Ending Balance
• Gains This Month
• Tax Extracted (37%)
• Deposit
• Cumulative Gains/Taxes
• Tax Reserve Account

2. Quarterly Summary CSV

Columns:

• Quarter (Y1Q1, Y1Q2, etc.)
• Starting Balance
• Deposits (3 months)
• Gains, Tax Reserved, Net Gains
• Ending Balance
• Tax Reserve Account

3. Monte Carlo Results JSON

Fields:

• final_balance: {mean, median, std, percentiles}
• milestones: {1M, 10M, 100M, 500M, 1B} probabilities
• risk_metrics: {riskofruin, prob_profit}
• all_paths: Array of all simulation paths

4. LaTeX Report (PDF)

Sections:

• Executive Summary
• Methodology
• Scenario Projections (tables)
• Monte Carlo Analysis (charts)
• Risk Analysis
• Tax Planning
• Recommendations

Integration Points

With Trading Analysis

Trading CSV → Edge Analysis → Win Rate / Avg Return
                           ↓
                    (Feed to forecasting)
                    - Use actual metrics
                    - Historical validation
                    - Baseline calibration

With Tax Planning

Forecast Results → Quarterly Gains → Tax Obligations
                                  ↓
                        (Generate payment schedule)
                        - 1040-ES forms
                        - Quarterly deadlines
                        - Reserve account

With Portfolio Analysis

Forecasts + Actuals → Track Performance → Identify Deviations
                                       ↓
                            (Adjust parameters monthly)
                            - Recalibrate projections
                            - Update assumptions
                            - Revise targets

Assumptions

Trading Assumptions

• Consistent daily returns at expected average
• Win rate maintained over time (90%)
• No catastrophic losses (5% stops enforced)
• Position sizing controlled (10% max)
• Deposits on schedule ($500/month)

Market Assumptions

• 20 trading days per month
• No extended market closures
• Liquidity sufficient for all positions
• No systematic regime changes

Tax Assumptions

• 37% federal reserve adequate
• Quarterly extraction on schedule
• No wash sale violations
• Short-term capital gains treatment

Limitations

1. Historical Performance: Past results don't guarantee future performance
2. Perfect Execution: Assumes no slippage or missed trades
3. No Black Swans: Doesn't model extreme market events
4. Linear Scaling: Assumes edge persists at all capital levels
5. No Capacity Constraints: Ignores liquidity limits

Risk Warnings

Exponential Growth Projections

• Year 3-5 projections are theoretical upper bounds
• Compounding assumptions may not hold indefinitely
• Market capacity constraints will limit growth
• Regulatory/tax changes not modeled

Position Sizing Critical

• Current 75% position sizing is unsustainable
• Must reduce to 10% max (per recommendations)
• Single bad trade can wipe out gains
• Risk management discipline essential

Tax Compliance Required

• Quarterly extraction must be disciplined
• Missing payments incurs penalties
• State tax varies significantly (NY vs FL)
• Professional CPA engagement recommended

Examples

Example 1: 3-Year Baseline Projection

Input: 18.5 trades/month at 3.58% average return

Output:

Year 1: $5.2M (from $2K + $6K deposits)
Year 2: $50B
Year 3: $3.2T

Tax Reserves: $800B (extracted quarterly)
Liquid Net Worth: $4.0T (portfolio + reserves)

Example 2: Monte Carlo (1,000 paths, 5 years)

Input: Same parameters, 1,000 simulations

Output:

Median Final Balance: $1.01B
95% Confidence Interval: $36.6M - $11.5B

Milestone Probabilities:
- $1M: 99.9%
- $100M: 96.2%
- $1B: 52.3%

Risk of Ruin: 0.0%
Max Drawdown: -8.2% (average)

Example 3: Tax Comparison (NY vs FL)

Input: $5M gains in Year 1

Output:

Federal Tax: $1.85M (37%)
NY State Tax: $537K (10.75%)
Total (NY): $2.39M (47.75%)

FL/TX Tax: $1.85M (37% federal only)
Tax Savings: $537K by relocating

Troubleshooting

Issue: Projections seem too high

Solution: These are theoretical upper bounds assuming perfect execution. Use Monte Carlo for realistic ranges.

Issue: Tax reserves insufficient

Solution: NY residents should use 45% reserve (not 37%). Adjust tax.quarterly_extraction_pct in config.

Issue: Monte Carlo paths diverge wildly

Solution: This is expected with exponential compounding. Focus on median/percentiles, not mean.

Issue: CSV export fails

Solution: Check write permissions to output directory. Default: ~/projects/portfolio/

Future Enhancements

• [ ] Drawdown recovery simulations
• [ ] Multi-strategy portfolio allocation
• [ ] Real-time parameter updates from live trading
• [ ] Options strategy forecasting
• [ ] Mean reversion edge modeling
• [ ] Correlation analysis (multi-symbol portfolios)
• [ ] Tax loss harvesting optimization
• [ ] Leverage/margin constraint modeling

References

Theory

• Kelly Criterion for position sizing
• Geometric mean vs arithmetic mean in compounding
• Log-normal return distributions
• Tax-adjusted performance metrics

Tools

• NumPy for Monte Carlo simulations
• Pandas for time series analysis
• PyYAML for configuration
• LaTeX for professional reports

Support

For issues:

1. Verify YAML config format
2. Check parameter ranges (win rate 0-100%, etc.)
3. Review log output for errors
4. Test with smaller scenarios first

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License: MIT (Part of astoreyai/claude-skills) Repository: https://github.com/astoreyai/claude-skills/

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: astoreyai
• Source: astoreyai/claude-skills
• License: MIT

Install and usage instructions live in the source repository linked above.